Terminal Subway Entry/Exit Detection with Accelerometer–Magnetometer Fusion
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Solution Overview
Problem
Existing technologies fail to accurately identify when a user gets on or off a subway carriage, affecting the user experience with intelligent terminals.
Innovation Solution
A method using acceleration and magnetometer data to determine a probability value for a subway state, enabling network acceleration when getting on, and displaying an exit card interface when getting off, with optional walking state consideration for enhanced accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only accelerometer data is used to determine terminal movement state, then the device complexity is low, but the measurement precision of subway state identification is insufficient
Solution Approach 1:
The patent combines accelerometer data and magnetometer data to determine terminal movement state. By merging multiple sensor data sources, the system achieves more accurate subway state identification while managing device complexity through integrated processing.
Solution Approach 2:
The patent introduces probability thresholds (first probability threshold, second probability threshold) to transform sensor data into actionable state determinations. By changing parameters from raw sensor values to probability-based decisions, the system improves measurement precision while maintaining manageable complexity.
2Ease of operation
If the terminal state identification is improved to accurately detect subway entry/exit, then the user experience is enhanced, but the loss of time for processing multiple sensor data increases
Solution Approach 1:
The patent pre-establishes probability thresholds and decision rules for determining subway states. By preparing the decision framework in advance with predefined thresholds, the system reduces real-time processing time while maintaining accurate user state detection for enhanced experience.
Solution Approach 2:
The patent replaces complex mechanical analysis of sensor data with a probability-based computational model. This substitution allows for faster processing of accelerometer and magnetometer data, reducing time loss while improving the accuracy of subway entry/exit detection for better user experience.
3Productivity
If the exit card function is automatically displayed upon detecting subway exit state, then the productivity of the service is improved, but the device complexity for state determination increases
Solution Approach 1:
The system automatically displays the exit card function when the subway exit state is detected through probability-based analysis of sensor data. This self-service approach improves service response efficiency by eliminating manual user actions while managing device complexity through automated decision-making algorithms.
Solution Approach 2:
The patent implements a feedback mechanism where sensor data continuously informs the state determination, which in turn triggers appropriate service responses. The probability-based state determination provides feedback that automatically activates the exit card function, improving productivity while the established feedback loop manages system complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Accurately identifies subway entry and exit states, providing timely exit card functionality and optimizing network connectivity, enhancing user experience.
Implementation Method 1
obtaining acceleration data of a terminal by using an acceleration sensor
Implementation Method 2
obtaining magnetometer data of the terminal by using a magnetometer sensor
Data Source
AI summary
A terminal state identification method and apparatus are provided, and are applied to the field of terminal technologies. The method includes: obtaining acceleration data and magnetometer data, determining a first probability value based on the acceleration data and the magnetometer data, then determining, with reference to the first probability value, a state of getting on/off a subway by a terminal user, and finally displaying a boarding code for exit to the user when determining the state of getting off a subway. In this way, it can be accurately identified whether the user is in the state of getting off a subway, and when the state of getting off a subway is identified, a to-be-used exit card function pops up for the user. This saves a time for the user to actively open an exit card, and provides a convenient service for the user.